Global Regions Research Articles

Phase and Amplitude Changes in Rainfall Annual Cycle Over Global Land Monsoon Regions Under Global Warming

AbstractLand monsoon rainfall has a distinct annual cycle. Under global warming, whether the phase and amplitude of this annual cycle would be changed is still unclear. Here, a global investigation is conducted using 34 CMIP6 and 34 CMIP5 models under a high emission scenario. Seasonal delays would occur in the Southern Hemisphere (SH) American (3.43 days), Northern Hemisphere (NH) African (5.98 days) and SH African (3.76 days) monsoon regions, while no robust signal is found in other monsoon regions. Except NH American monsoon, amplitude is enhanced in all the monsoon regions. Compared to amplitude, the phase changes dominate the future changes of precipitation in the SH American, NH African and SH African monsoon regions. In these phase‐dominated regions, atmospheric energetic framework is proved to be reliable at regional scale and the enhanced effective atmospheric heat capacity is found to be the dominant factor.

Trends, turning points, and driving forces of desertification in global arid land based on the segmental trend method and SHAP model

ABSTRACT Desertification is a form of land degradation observed in arid, semiarid, and dry subhumid ecosystems. Assessing the global trends and drivers of desertification in arid land is crucial for developing effective land restoration policies and mitigating desertification. We aimed to evaluate global segmental trends in desertification in arid land using Moderate Resolution Imaging Spectroradiometer images from 2000 to 2022. By constructing a robust MSAVI-Albedo Desertification Distance Index (DDI), we assessed the segmented development characteristics of desertification on Google Earth Engine. Additionally, we employed the SHapley Additive exPlanations (SHAP) model and machine learning methods to analyze the individual and interactive driving mechanisms of desertification. The results indicated an overall reduction in desertification, with approximately 23.21 million km2 (39% of the global arid region area) exhibiting negative trends in DDI. Approximately 31% of the land area showed a DDI of −0.002/y. Precipitation was consistently the primary factor influencing desertification, with an average SHAP value of 11.42. Secondary influencing factors included potential evapotranspiration, soil moisture, and vapor pressure differences. Notably, the coupling between precipitation and soil moisture exhibited the most significant impact on the desertification process, with SHAP coupling values of approximately 3.28 and 5.06 before and after the DDI turning point, respectively. These findings provide new insights into desertification on a global scale and offer valuable scientific support for promoting effective prevention and control measures.

Variations in the anatomical structure of the pterion among populations from various global regions

Anatomical variations in the structure of the pterion were examined in various craniological series represent-ing modern populations from Australia, Melanesia, Southeast Asia, North Asia, America, and Europe, encom-passing 2035 adult crania. The comparison of populations based on the frequency of nonmetric traits revealed significant diversity across regions. Notably, the sphenoparietal connection is most frequent in European and South Asian populations, as well as among Native Americans, while it is least common among African groups. The frontotemporal connection predominates among Australian Aborigines and Melanesians and is also common in African populations but is almost non-existent in Europeans. The X-shaped pterion is most frequently observed in the Eskimos of Chukotka and the Chukchi, as well as among Somali and Tanzanian populations. A high fre-quency of epipteric bones is particularly characteristic of Southern Indians, Burmese, Australians, and Melane-sians. Pairwise comparisons of populations were conducted using Smith's Mean Measure of Divergence (MMD). To visualize the data from individual regions, the method of Multidimensional Scaling (MDS) was applied to the matrices of biological distances. The MDS plot for the North Asian region revealed distinct clusters of the Arctic, Baikal, Cen-tral Asian, and Ural groups, aligning with G.F. Debetz's classification based on morphological similarities among populations. In the MDS plot for the South and Southeast Asian, American, and African populations, Australians and Melanesians formed a separate cluster; Pueblo Indians were closely aligned with Peruvians, South Indians with Burmese, Malays merged with Papuans, and African populations were positioned relatively close to each other. In Europe, Caucasian groups formed a distinct cluster. On the combined graph, the populations were clearly divided by regions. The results obtained indicate that the spatial arrangement of populations on the graphs approximately mir-rors their genetic connections and shared origins. This suggests that nonmetric variations in the pterion area are more likely determined by genetic rather than ecological factors and can be considered taxonomically valuable traits at the regional level. Investigating the structure of the pterion in an evolutionary context may shed light on broader questions concerning the evolution of the skull and the mechanisms influencing its formation.

Health workforce for oral health inequity: Opportunity for action.

Oral health is high on the global agenda following the adoption of the 2022 global strategy on oral health at the 75th World Health Assembly. Given the global burden of oral disease, workforce development to achieve universal health coverage [UHC] is crucial to respond to population needs within the non-communicable disease agenda. The aim of this paper is to present an overview of the oral health workforce [OHWF] globally in relation to key contextual factors. Data from the National Health Workforce Accounts and a survey of World Health Organization [WHO] member states were integrated for analysis, together with country-level data on population and income status. Data are presented using the WHO categorisation of global regions and income status categories established by the World Bank. Workforce densities for key OHWF categories were examined. Multiple regression was used to model workforce density and contextual influences. Challenges and possible solutions were examined by country income status. There are approximately 3.30 dentists per 10,000 population globally, and a combined OHWF [dentists, dental assistants/therapists and dental prosthetic technicians] of 5.31 per 10,000. Marked regional inequalities are evident, most notably between WHO European and African regions; yet both make greater use of skill mix than other regions. When adjusted by region, 'country income status' and 'population urbanization' are strong predictors of the workforce density of dentists and even more so for the combined OHWF. Maldistribution of the workforce [urban/rural] was considered a particular workforce challenge globally and especially for lower-income countries. Strengthening oral health policy was considered most important for the future. The global distribution of dentists, and the OHWF generally, is inequitable, with variable and limited use of skill mix. Creative workforce development is required to achieve the global oral health agenda and work towards equity using innovative models of care, supported by effective governance and integrated policies.

Perspectives on animal experimentation in herbal medicine research: ethical dilemmas and scientific progress

Animal experimentation has long been an integral part of biomedical and cosmetics research, with historical roots dating back to ancient Greece. During that period, physicians constrained by cultural taboos that forbade the use of human cadavers, turned to the dissection of animals for their anatomical studies. The use of specific animal models in research has often been justified by the remarkable biological similarities between animals and humans. However, there are instances where animal models, such as fish and frogs, are used, despite significant disparities in their anatomy and physiology compared to humans. In herbal medicine research, animal experimentation has found various applications. Numerous plant species from diverse global regions, including the United Kingdom, United States, China, India, and Africa, have been studied to identify their pharmacological properties and therapeutic indications. Nevertheless, the use of animals in these studies, while offering undeniable advantages, remains a subject of intense debate and contention, mainly arising from the ethical challenges it presents, as well as the substantial financial burden it imposes, and its inability to reliably predict human responses. This paper, therefore, proposes a comprehensive list of research methodologies that are ethical, practical, cost-effective, and consistent with the real ethos of herbal medicine. These alternative methods, which include in vitro studies, human cell cultures, computational modelling, culturally sensitive clinical trials, and ethnobotanical surveys, have the potential to provide cost-effective healthcare solutions, without subjecting animals to unnecessary suffering.

Regarding the Pain of Indigenous Others

Cities are real, physical, material concentrations of human activities and built environments, but they are also portals that allow and require unique ways of perceiving relations across space and time. Photography, especially the genre of seductive urban landscape views so often deployed by airlines, realtors, and city boosters, distorts our perceptions of space-time. These distortions are particularly serious in the unique configuration of Indigeneity and transnationalization that constitutes the lands presently known as Canada and British Columbia. Drawing inspiration from Sontag's dark but essential Regarding the Pain of Others, and focusing on the Vancouver global city region, this article seeks to develop critical captions for urban landscape views as what Eugène Atget portrayed as crime-scene evidence.

Societal impacts of marine nitrogen pollution: rapid evidence assessment and future research

Nitrogen pollution is a global problem and to effectively mitigate the effects we need to understand both the ecological and societal impacts. Coral reefs are of particular concern, as they are a critical source of livelihoods, culture, and wellbeing for hundreds of millions of people. Yet they are rapidly declining due to numerous pressures, with nitrogen pollution identified as a top-ranked non-climatic pressure. A Rapid Evidence Assessment was carried out to understand the societal impacts derived from marine nitrogen pollution on coral reefs. The results highlight key research evidence gaps, such as unclear reporting of nitrogen pollution, not distinguishing impacts from nitrogen and other stressors, non-quantification of nitrogen-specific marine and societal impacts, unstudied global regions with high nitrogen pressure, and the need for greater awareness on marine nitrogen pollution. Future research questions are proposed to allow better understanding on how tropical coastal societies are being impacted by marine nitrogen pollution.

Shaping green regionalism: New trade law approaches to environmental sustainability

AbstractGreen regionalism aims to mutually reinforce environmental governance and economic integration. The article provides the first analysis of green regionalism in international law. It argues that green regionalism represents a paradigm shift in global normative endeavours towards environmental sustainability. By contextualising three waves of global regionalism, the article unveils the evolving architecture of green regionalism alongside negotiations of the World Trade Organization and multilateral environmental agreements. Moreover, it sheds light on the pertinent disputes and features of new green initiatives galvanised by the European Union, the United States and Asia‐Pacific countries. These developments are pivotal in understanding the trade‐environment nexus and fostering economic resilience in our hyperconnected world.

Comparative assessment of dry- and humid-heat extremes in a warming climate: Frequency, intensity, and seasonal timing

Dry and humid-heat extremes are two types of heat extremes, each exhibiting unique climatological characteristics and impacts on different sectors of society. Using historical simulations and projections produced under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) by models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we show a comparative assessment of the future changes in dry- and humid-heat extremes over global land. Relative to 1995–2014, projections for the mid-term future (2041–2060) and long-term future (2081–2100) periods suggest that most global regions will experience an increase in frequency and intensity of both dry- and humid-heat extremes, especially the tropical regions. In these future periods, the peak occurrences of dry- and humid-heat extremes in mid-to high-latitude regions often occur within the same month. However, there will be a one-to two-month gap between the peak occurrences of dry- and humid-heat extremes in tropical regions, primarily due to monsoonal circulations that introduce variability by causing dry-heat extremes before the onset of monsoons and humid-heat extremes as the monsoons commence. This suggests the need for sector-specific adaptation strategies during different periods of the year for tropical regions. Under both future scenarios, whether considering individual exposure or land area, the average level of exposure to extreme humid-heat days is projected to increase more significantly compared to dry-heat days. The above results highlight the risks associated with the intensification of humid heat in future climate scenarios and warrant the development of effective strategies to mitigate the adverse effects.

DSTAN: A Deformable Spatial-temporal Attention Network with Bidirectional Sequence Feature Refinement for Speckle Noise Removal in Thyroid Ultrasound Video.

Thyroid ultrasound video provides significant value for thyroid diseases diagnosis, but the ultrasound imaging process is often affected by the speckle noise, resulting in poor quality of the ultrasound video. Numerous video denoising methods have been proposed to remove noise while preserving texture details. However, existing methods still suffer from the following problems: (1) relevant temporal features in the low-contrast ultrasound video cannot be accurately aligned and effectively aggregated by simple optical flow or motion estimation, resulting in the artifacts and motion blur in the video; (2) fixed receptive field in spatial features integration lacks the flexibility of aggregating features in the global region of interest and is susceptible to interference from irrelevant noisy regions. In this work, we propose a deformable spatial-temporal attention denoising network to remove speckle noise in thyroid ultrasound video. The entire network follows the bidirectional feature propagation mechanism to efficiently exploit the spatial-temporal information of the whole video sequence. In this process, two modules are proposed to address the above problems: (1) a deformable temporal attention module (DTAM) is designed after optical flow pre-alignment to further capture and aggregate relevant temporal features according to the learned offsets between frames, so that inter-frame information can be better exploited even with the imprecise flow estimation under the low contrast of ultrasound video; (2) a deformable spatial attention module (DSAM) is proposed to flexibly integrate spatial features in the global region of interest through the learned intra-frame offsets, so that irrelevant noisy information can be ignored and essential information can be precisely exploited. Finally, all these refined features are rectified and merged through residual convolution blocks to recover the clean video frames. Experimental results on our thyroid ultrasound video (US-V) dataset and the DDTI dataset demonstrate that our proposed method exceeds 1.2 1.3dB on PSNR and has clearer texture detail compared to other state-of-the-art methods. In the meantime, the proposed model can also assist thyroid nodule segmentation methods to achieve more accurate segmentation effect, which provides an important basis for thyroid diagnosis. In the future, the proposed model can be improved and extended to other medical image sequence datasets, including CT and MRI slice denoising. The code and datasets are provided at https://github.com/Meta-MJ/DSTAN .

Comparative analysis of natural resistance-associated macrophage protein 1 gene expression and anti-PGL-1 antibodies in multibacillary leprosy and household contacts.

Leprosy continues to pose a significant challenge to public health, particularly in certain global regions. Accurate diagnosis and understanding of the disease's etiology are crucial for effective management and prevention. This study aimed to explore the contribution of Natural resistance-associated macrophage protein 1 (NRAMP1) and its genetic variations, as well as the levels of anti-PGL-1 antibodies, to the pathology of multibacillary leprosy in affected individuals and their household contacts. The study included 23 multibacillary leprosy patients and 28 household contacts. NRAMP1 protein expression and anti-PGL-1 IgG and IgM levels were measured using PCR and ELISA techniques, respectively. Genotypic variants of the NRAMP1 gene were also examined. Statistical analyses, including Mann-Whitney tests and univariate logistic regression, were employed to evaluate the data. Significant differences were observed in NRAMP1 protein expression and IgG and IgM levels between the patient and household contact groups. The study also highlighted the role of the NRAMP1 gene and its D543N and 3'UTR polymorphisms in leprosy susceptibility. No significant differences were observed in the genotype variants of INT4 between the two groups. These findings emphasize the potential of integrating PCR technology with serological tests to enhance diagnostic precision in leprosy. They also suggest the need for further research to clarify the role of NRAMP1 and its polymorphisms in leprosy susceptibility and resistance.

Alterations of pathogen transmission patterns and attenuated immune stimulation might be the cause of increased adult respiratory infections cases in 2023, results from a multi-center study in mainland China

BackgroundSeveral respiratory infections outbreaks have been observed in mainland China after reduction of non-pharmaceutical interventions. Other countries have seen increases in respiratory infections outside typical seasons post-COVID-19, warranting investigation into underlying causes. MethodsWe established monitoring networks for suspected respiratory infection in 14 tertiary hospitals nationwide. PCR for SARS-CoV-2, influenza A and B were performed on 3708 respiratory specimens and deep sequencing were conducted to identify co-infections or newly emerging microbes in 2023. Viral evolutionary analysis was completed. We retrospectively detected serum antibody level for various respiratory pathogens from 4324 adults without respiratory infections over 7 years to observe its dynamic curves. FindingsSARS-CoV-2 and influenza A were the main pathogens during outbreaks in 2023, bacterial-virus and bacterial-bacterial co-infections were most detected, but community co-infections didn't significantly increase pneumonia incidence. Different SARS-CoV-2 and influenza variants were present in different outbreaks, and no novel pathogens were found. The epidemiological patterns of influenza A, COVID-19 and etc. were altered, exhibiting characteristics of being "staggered" compared to most global regions, and potentially led to "overlapping prevalence". Binding antibody testing showed regular fluctuation, without significant decrease against common respiratory pathogens in adults. Influenza A antibody stimulation was attenuated during the 2023 outbreak. Conclusions"Misaligned" alteration in seasonal respiratory disease patterns possibly caused combined epidemics, leading to cases spike in China, 2023. In adults, antibody levels didn't show significant decline, but reduced immune response to influenza during 2020–2023 emphasizes the need for consistent vaccination during pandemics.

Navigating the Present and Future Dynamics of Electric Vehicle Fast Charging and its Impact on Grid

As electric vehicle (EV) adoption surges worldwide, the need for fast charging infrastructure becomes paramount. Fast charging technology alleviates range anxiety and bolsters EV practicality. This comprehensive analysis delves into current challenges and future prospects surrounding EV fast charging and its grid impact. Examining the state of fast charging technology, it scrutinizes charging standards, connector types, and power levels across global regions. Emphasis is placed on key market players and the imperative for interoperability and standardization to seamlessly integrate EVs into the power grid. Voltage fluctuations, harmonics, and power factor issues stemming from rapid, high-power charging pose technical hurdles. Solutions like advanced power electronics, grid management tactics, and enhanced communication between EVs and the grid are explored to uphold stability and power quality. Consideration is given to energy sources fueling fast chargers, including renewable integration and environmental repercussions. Economic facets, encompassing infrastructure deployment costs and grid upgrade analyses, are examined amidst escalating electricity demand and potential grid expansion needs. A forward-looking perspective addresses future challenges and opportunities. This includes advancements in battery tech, smart grid solutions, and bidirectional power flow potential between EVs and the grid. Index Terms: Battery electric vehicles (BEVs), Grid, Fast Charging, plug-in hybrid electric vehicles (PHEVs).

Current Management of Allergic Rhinitis

Allergic rhinitis (AR) is the most common allergic disease worldwide and one of the most common chronic diseases in general. Allergic rhinitis is caused by inhalant allergens from outdoor and indoor environments with varying significance of different allergens in global regions. We provide options for the current management for AR including pharmacological treatments and nonpharmacological options and allergen immunotherapy (AIT). A literature review has been conducted in Medline, Pubmed, as well as the national and international study (ClinicalTrials.gov) and guideline registers and the Cochrane Library. Human studies published on the topic in the period up to and including November 2023 were taken into account. Allergen avoidance measures, pharmacotherapy, and AIT are the cornerstones of AR treatment. Nonpharmacological measures and behavioral recommendations should be adequately added. Tools of precision medicine are already playing a significant role and will be part of the diagnostic and therapeutic standard in the future. Patients benefit most in a network of different pharmacological and nonpharmacological treatment measures including AIT. Application of precision medicine tools for diagnosis and treatment will improve standards of care.

Cycling of fluid-mobile elements through the forearc: Insights from the Cl, B, and Li isotope composition of Costa Rican spring fluids

Loss of slab-derived volatile and fluid-mobile elements (FME) through the forearc may represent a large, unaccounted for flux out of convergent margins. To address volatile recycling through the forearc and potential changes in fluid source from the progressively dehydrating subducting slab, we collected water samples from 44 different cold and thermal (>40 °C) springs on a transect across the outer forearc (∼20–40 km to the subducting slab), forearc (∼40–80 km to the slab), and arc (∼80–120 km to the slab) in Costa Rica. We focused on the heavy halogens (Cl, Br, I), as well as B and Li, given their high fluid mobility and thus limited potential for modification by subsequent fluid-rock interaction. Chlorine, boron, and lithium stable isotope ratios show dramatic ranges from −1.7 to +1.0 ‰ (n = 43), −12.0 to +30.9 ‰ (n = 35), and −2.4 to + 27.5 ‰ (n = 38), respectively, with distinct changes across the transect consistent with a sedimentary pore fluid component in the outer forearc, fluids sourced from dehydration of the slab (sediment and altered oceanic crust) in the forearc, and minimal slab input near the arc. Variations in elemental ratios (Br/Cl, I/Cl, B/Cl, Li/B) across the transect are also largely consistent with evolving FME sources during subduction. Boron isotope ratios in some higher-temperature fluids are modified due to phase separation, whereas, lithium and chlorine isotope ratios are minimally modified. Springs located in the outer forearc along a major fault (Falla Morote) deviate from the consistent across-arc trend and record almost the full range of observed isotopic values. This extreme range in values along the fault likely represents a combination of adsorption/desorption effects, weathering, and mixing with crustal fluids. Mass balance calculations show that up to ∼ 70 % of Cl, ∼50 % of Br, ∼30 % of B, ∼15 % of I, and minimal Li may be recycled through the outer forearc and forearc springs of the Costa Rican margin, therefore fluid emission via springs in global forearc regions are a potentially significant output for FME at convergent margins.

Trajectory planning of a closed five-bow-shaped bar linkage based on finite Fourier series

With aim to reduce the energy consumption, a trajectory planning method is presented for a closed five-bow-shaped bar linkage, which can be propelled itself by morphing configuration. The objective herein is to optimize the driving joints trajectories within the global feasible region when the linkage rolls along the ground with a desired acceleration. The driving joint trajectories were represented by finite Fourier series, whose coefficients were solved by genetic algorithm to ensure a minimal energy consumption of the linkage. The impact of the number of terms of finite Fourier series on the energy consumption was also discussed through numerical examples. As a result, the energy consumption based on this strategy had been reduced by 19%, comparing with the constant potential energy strategy. A number of terms between six and eight using to denote the joint trajectories are appropriate, because that a small number of terms is incapable of expressing the joint trajectories accurately, whereas, a large number makes the joints to be subjected to vibration shock. At last, simulation on a virtual model and experiments on a prototype were carried out to verify the effectiveness of the proposed method.

Development of a Distributed Physics‐Informed Deep Learning Hydrological Model for Data‐Scarce Regions

AbstractClimate change has exacerbated water stress and water‐related disasters, necessitating more precise streamflow simulations. However, in the majority of global regions, a deficiency of streamflow data constitutes a significant constraint on modeling endeavors. Traditional distributed hydrological models and regionalization approaches have shown suboptimal performance. While current deep learning (DL)‐related models trained on large data sets excel in spatial generalization, the direct applicability of these models in certain regions with unique hydrological processes can be challenging due to the limited representativeness within the training data set. Furthermore, transfer learning DL models pre‐trained on large data sets still necessitate local data for retraining, thereby constraining their applicability. To address these challenges, we present a physics‐informed DL model based on a distributed framework. It involves spatial discretization and the establishment of differentiable hydrological models for discrete sub‐basins, coupled with a differentiable Muskingum method for channel routing. By introducing upstream‐downstream relationships, model errors in sub‐basins propagate through the river network to the watershed outlet, enabling the optimization using limited downstream streamflow data, thereby achieving spatial simulation of ungauged internal sub‐basins. The model, when trained solely on the downstream‐most station, outperforms the distributed hydrological model in streamflow simulation at both the training station and upstream held‐out stations. Additionally, in comparison to transfer learning models, our model requires fewer gauge stations for training, but achieves higher precision in simulating streamflow on spatially held‐out stations, indicating better spatial generalization ability. Consequently, this model offers a novel approach to hydrological simulation in data‐scarce regions, especially those with poor hydrological representativeness.

Application of Cognitive Load Theory in VR Development and Its Impact on Learning: A Perspective on Prior Knowledge, Learning Interest, Engagement, and Content Comprehension

This research examines the utilization of Virtual Reality (VR) and its implications for the learning process, specifically focusing on learning interest, prior knowledge, learning engagement, and content comprehension. The central objective is to establish a comprehensive model that unravels the intricate interplay between these factors within the context of VR-based learning. The study also aims to shed light on the impact of integrating Cognitive Load Theory into VR development and its effects on the learning experience. Adopting an observational design, this study elucidates the intricate relationships among learning interest, prior knowledge, learning engagement, and content comprehension in VR-based education. The VR technology employed in this research has previously undergone rigorous feasibility testing. The VR application was designed following cognitive load theory principles. Its immersive content offers users a lifelike immersion into the natural habitats of diverse animal species across various global regions. By leveraging VR technology, elementary school students engage in a more profound and authentic learning journey. A total of 85 participants, encompassing fourth and fifth-grade elementary school students, were involved in the study. These students were drawn from schools situated in rural areas in particular regions in Indonesia and had moderate to low economic backgrounds. The variables under examination include Prior Knowledge, Learning Interest, Engagement, and Content Comprehension as learning outcomes. Data analysis was conducted utilizing a blend of linear regression and path analysis techniques, with a confidence level of 95%. The Guttman scale questionnaire was used, and total scores were transformed into a ratio scale through a conversion process. The study reveals a positive correlation between learning interest and learning outcomes, highlighting that a strong interest in a subject contributes to improved learning results. Additionally, both learning interest and prior knowledge influence learning engagement. Students with higher learning interests and prior knowledge are more likely to actively engage in the learning process actively, underscoring internal factors' role in motivating participation. Learning engagement moderates the relationships between learning interest, prior knowledge, and learning outcomes. By enhancing the effect of learning interest and prior knowledge on learning outcomes, engagement enables more comprehensive and practical information processing.

Improved Electronic Medical Record Documentation

Clozaril, a psychiatric medication, is the focus of this report. The allocated brand names for this medicine in the United Kingdom are; Clozaril, Fazaclo, and Versaclo. Its generic name as detailed by the DRUGBANK Online is (2022) is Clozapine. Clozaril is also known by different names including Leponex, Azaleptin, Fazaclo, Froidir, Klozapol and Clopine in other global regions.

Modifiable work stress factors and psychological health risk among nurses working within 13 countries.

Nurses are identified as having higher work stress and poor mental health risk among health care workforce globally. It remains unclear which modifiable stress factors pose the greatest risk for poor psychological health among nursing workforce and needed to inform targeted practice and policy change. To determine which occupation-related or personal stress factors precipitate higher risk for burnout, depression, anxiety, job satisfaction or intention to leave one's position among nurses globally. A cross-sectional anonymous survey was administered via email using a snowball recruitment strategy. Academic researchers and clinical industry leaders across 3 global regions collaborated to generate an email listserv of professional nursing contacts for survey distribution. The survey included valid and reliable measures to scale stress factors (Work Stress Questionnaire), and screen for burnout (single item), depression (Patient Health Questionnaire-2), anxiety (Generalized Anxiety Disorder-2), resilience (Brief Resilience Scale) and intention to leave one's job (single item). We used logistic regression, first unadjusted and then adjusted for personal and professional characteristics, to determine associations between stress factors and psychological health risk. The final sample consisted of responses from 2864 nurses working across 13 countries. Most respondents reported working as a clinical nurse in the Philippines (n = 2275), United States (n = 424) and Saudi Arabia (n = 104). One third of nursing respondents endorsed high burnout and intention to leave their job. Those reporting work conflict had significantly higher odds of burnout (odds ratio 3.18; 95% CI 2.22-4.54) and three times more likely to screen positive for depression (odds ratio 3.02; 95% CI 1.36-6.72) and anxiety (odds ratio 2.92; 95% CI 1.57-5.43). Those endorsing difficulty sleeping were 15 times more likely to screen positive for depression (odds ratio 15.63; 95% CI 2.09-117.06). Lack of social support was significantly associated to higher risk for burnout, job dissatisfaction, depression, anxiety, and intention to leave one's position. Nurses remain at risk for burnout and poor psychological health stemming from work stress. Factors such as clear workplace goals and assignments, increased engagement, good sleep health and social support may serve as protective factors against suboptimal psychological health, and in-turn poor workforce retention. Nurses reporting conflict in the workplace are three times more likely to screen positive for burnout, depression, and anxiety. Nurses reporting difficulty sleeping are 15 times more likely to screen positive for depression. Several modifiable factors can be targeted to reduce poor psychological health and high workforce turnover among nurses across countries.